A Fuzzy Clustering Method of Color Image With Semantic Color Tree

DOI

10.2991/iccsee.2013.418How to use a DOI?

Keywords

fuzzy clustering, semantic color, semantic tree, color extraction

Abstract

Fuzzy clustering algorithms have been widely used for image segmentation, typically such as FCM algorithm. However, the FCM algorithm is parameter sensitive, and its results lack of availability. To improve the above problems, a novel fuzzy clustering method based on semantic color tree for image segmentation is proposed in this paper. The method is realized by modifying the membership function in the conventional FCM algorithm and by constructing the semantic color tree to achieve the semantic color extraction, which take human visual subjectivity into account in semantics. The proposed method is applied to real images. Experimental results show that the presented algorithm performs more effectively than the FCM algorithm.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiaofeng Wang
AU  - Jianhua Li
PY  - 2013/03
DA  - 2013/03
TI  - A Fuzzy Clustering Method of Color Image With Semantic Color Tree
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 1669
EP  - 1673
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.418
DO  - 10.2991/iccsee.2013.418
ID  - Wang2013/03
ER  -